AI and machine learning systems are only as good as the data we feed them. Witness the fallout from the COVID-19 crisis, which threw many AI algorithms out of whack: 'If machines are to be trusted, we need to watch over them.'
Artificial intelligence and machine learning models can work spectacularly -- until they don't. Then they tend to fail spectacularly. That's the lesson drawn from the COVID-19 crisis, as reported in MIT Technology Review. Sudden, dramatic shifts in consumer and B2B buying behavior are, as author Will Douglas Heaven put it, "causing hiccups for the algorithms that run behind the scenes in inventory management, fraud detection, marketing, and more. Machine-learning models trained on normal human behavior are now finding that normal has changed, and some are no longer working as they should."
By Joe McKendrick for Service Oriented on ZDNet